Effects of Protein Content and Composition on White Noodle Making Quality: Color
Bibliographic record
Abstract
ABSTRACT Wheat cultivars, representing three winter and three spring wheats were grown in western Canada with six levels of nitrogen fertilizer and flours were prepared from them with an extraction rate of 65%. Using a chromameter, flour color and the color of uncooked white noodle sheets made from these flours with different resting times were assessed. The cooked noodle sheet color was also assessed. While protein content initially declined with added nitrogen and increased with further nitrogen addition, brightness ( L *) of flour decreased and redness ( a *) and yellowness ( b *) increased. Positive correlation coefficients of flour brightness with particle size index (PSI) were also observed. Flour redness ( a *) and yellowness ( b *) were also affected by flour moisture content, whereas L * values were not significantly correlated with moisture contents. For the uncooked white noodle sheet, as protein content increased brightness decreased but there was an increase in a * and b * values. Thus, the L * value for noodle sheets was negatively correlated with the a * and b * values. The percentages of monomeric protein and soluble glutenin in flour were equal to or better than protein content in relation to most noodle sheet color characters. Uncooked noodle sheet brightness decreased, while redness and yellowness increased with rest time. In general, uncooked white noodle sheets prepared from different wheat flours can be ranked in terms of brightness and yellowness within each level of nitrogen fertilization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".